Air-conditioning system and method for controlling air-conditioning apparatus

ABSTRACT

An air-conditioning system includes an air-conditioning apparatus, a user-detecting unit detecting, for users, an amount of activity and a position, a storage device storing, for each amount of activity, a group including comfort index distributions each corresponding to each of air-conditioning control patterns of the air-conditioning apparatus, and a controller configured to obtain an air-conditioning control pattern that enables a comfort efficiency to be maximum, by specifying the group corresponding to the amount of activity for each of the users, extracting the comfort indexes corresponding to the position of each of the users from the comfort index distributions in the specified group, and, based on the comfort indexes extracted corresponding to the position of each of the users, calculating the comfort efficiency indicating a comprehensive comfort level of the users for each of the air-conditioning control patterns.

CROSS REFERENCE TO RELATED APPLICATION

This application is a U.S. National Stage Application of International Application No. PCT/JP2020/015040 filed on Apr. 1, 2020, the contents of which are incorporated herein by reference.

TECHNICAL FIELD

The present disclosure relates to an air-conditioning system conditioning air in an air-conditioned space and a method for controlling an air-conditioning apparatus.

BACKGROUND

In recent years, due to effects of change in an outside environment such as global warming, demand for improving a comfort level in a living environment is increased. For air-conditioning apparatuses, keeping thermal comfort for people staying indoors becomes more important. To achieve the comfortableness, a comfort index called the predicted mean vote (PMV) was proposed. An air-conditioning control system that controls an air-conditioning apparatus by monitoring the PMV of a user in an air-conditioned space is disclosed (for example, see Patent Literature 1).

When performing a local air-conditioning in which airflow is locally supplied to a demander, the air-conditioning control system disclosed in Patent Literature 1 performs the local air-conditioning in such a manner that the PMV of an adjacent person, who stays at a certain distance away from the demander, is kept within a predetermined range while the PMV of the demander is kept within a predetermined range. The air-conditioning control system disclosed in Patent Literature 1 weakens the local air-conditioning when the PMV of the adjacent person falls outside the predetermined range.

PATENT LITERATURE

-   Patent Literature 1: International Publication No. 2008/087959

When the PMV of the adjacent person falls outside the predetermined range, the air-conditioning control system disclosed in Patent Literature 1 performs control in such a manner that a comfort level of the adjacent person is given priority over that of the demander and the local air-conditioning is thus weakened. In this case, because the local air-conditioning is weakened, it takes time until the PMV of the demander enters the predetermined range. During that time, the demander has to tolerate an uncomfortable condition. In a case where there are a plurality of users in the air-conditioned space, when the air-conditioning control system disclosed in Patent Literature 1 improves comfort levels of some users, comfort levels of the other users are impaired.

SUMMARY

The present disclosure has been made to overcome the above-mentioned problem, and an object thereof is to provide an air-conditioning system that improves comfort levels of a plurality of users in an air-conditioned space and a method for controlling an air-conditioning apparatus.

An air-conditioning system according to one embodiment of the present disclosure includes an air-conditioning apparatus conditioning air in an air-conditioning target space, a user-detecting unit detecting, for a plurality of users in the air-conditioning target space, an amount of activity of each of the plurality of the users and a position of each of the plurality of the users in the air-conditioning target space, a storage device storing, for each of a plurality of amounts of activity, a group including a plurality of comfort index distributions each being a distribution of comfort indexes each indicating a user comfort level in the air-conditioning target space, the plurality of the comfort index distributions each corresponding to each of a plurality of air-conditioning control patterns of the air-conditioning apparatus, and a controller configured to obtain, from the plurality of the air-conditioning control patterns, an air-conditioning control pattern that enables a comfort efficiency to be maximum, by specifying the group corresponding to the amount of activity detected by the user-detecting unit for each of the users, extracting, from the plurality of the comfort index distributions in the specified group, a plurality of the comfort indexes corresponding to a position detected by the user-detecting unit, and, based on the plurality of the comfort indexes extracted in correspondence of the detected position of each of the users, calculating the comfort efficiency indicating a comprehensive comfort level of the users for each of the plurality of the air-conditioning control patterns.

A method for controlling an air-conditioning apparatus according to another embodiment of the present disclosure is performed by a controller being connected to a user-detecting unit detecting, for a plurality of users in an air-conditioning target space, an amount of activity of each of the plurality of the users and a position of each of the plurality of the users in the air-conditioning target space, and also to a storage device. The control method includes steps of storing, for each of a plurality of amounts of activity, a group including comfort index distributions each being a distribution of comfort indexes each indicating a user comfort level in the air-conditioning target space, the comfort index distributions each corresponding to each of a plurality of air-conditioning control patterns of the air-conditioning apparatus, specifying the group corresponding to the amount of activity detected by the user-detecting unit for each of the users, extracting, from the plurality of the comfort index distributions in the specified group, a plurality of the comfort indexes corresponding to the position detected by the user-detecting unit for each of the users, calculating a comfort efficiency indicating a comprehensive comfort level of the plurality of the users for each of the plurality of the air-conditioning control patterns based on the plurality of the comfort indexes extracted in correspondence of the position of each of the users, and obtaining, from the plurality of the air-conditioning control patterns, an air-conditioning control pattern that enables the calculated comfort efficiency to be maximum.

According to one embodiment of the present disclosure, the group including comfort index distributions in the air-conditioning target space each corresponding to each of the plurality of the air-conditioning control patterns is determined corresponding to the amount of activity of each of the users in the air-conditioning target space. In addition, the plurality of the comfort indexes each corresponding to the position of each of the users in the air-conditioning target space are extracted from the plurality of the comfort index distributions in the group. Then, based on the plurality of the comfort indexes of each of the users, the air-conditioning control pattern that enables the comfort efficiency for the plurality of the users to be maximum is obtained from the plurality of the air-conditioning control patterns. When the air-conditioning apparatus conditions air according to the air-conditioning control pattern that enables the comfort efficiency for the plurality of the users to be maximum, the comfort levels for the users can be improved.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a diagram illustrating a configuration example of an air-conditioning system according to Embodiment 1.

FIG. 2 is a refrigerant circuit diagram illustrating a configuration example of an air-conditioning apparatus shown in FIG. 1 .

FIG. 3 is a schematic diagram viewed from a side, illustrating a configuration example of a load-side unit shown in FIG. 2 .

FIG. 4 is a schematic diagram illustrating a relationship between an angle of a first flap shown in FIG. 3 and an air blow direction.

FIG. 5 is a schematic diagram illustrating a relationship between an angle of a second flap shown in FIG. 3 and an air blow direction.

FIG. 6 is a diagram illustrating an example of a range of temperature distribution in a vertical direction to be detected by an infrared sensor shown in FIG. 2 .

FIG. 7 is a diagram illustrating an example of a range of temperature distribution in a horizontal direction to be detected by the infrared sensor shown in FIG. 2 .

FIG. 8 is an image diagram illustrating an example of a case where a distribution of temperatures detected by the infrared sensor shown in FIG. 2 is shown as a two-dimensional image.

FIG. 9 is a functional block diagram illustrating a configuration example of a controller shown in FIG. 2 .

FIG. 10 is a hardware configuration diagram illustrating a configuration example of the controller shown in FIG. 9 .

FIG. 11 is a hardware configuration diagram illustrating another configuration example of the controller shown in FIG. 9 .

FIG. 12 is a functional block diagram illustrating a configuration example of a controller of an information processing device shown in FIG. 1 .

FIG. 13 is a table illustrating an example in which types of activities and corresponding energy metabolism rates, each representing a typical amount of activity, are listed.

FIG. 14 is a hardware configuration diagram illustrating a configuration example of an arithmetic device shown in FIG. 12 .

FIG. 15 is a layout diagram illustrating an example of an air-conditioning target space in which the air-conditioning apparatus shown in FIG. 1 conditions air.

FIG. 16 is a table illustrating an example of activity amounts and positions of users.

FIG. 17 is a schematic diagram illustrating an operation procedure of the information processing device according to Embodiment 1.

FIG. 18 is a flowchart illustrating an operation procedure of the information processing device according to Embodiment 1.

FIG. 19 is a table illustrating an example of calculation results of comfort efficiency.

FIG. 20 is an image diagram illustrating an example of IPMV distribution for an air-conditioning control pattern determined in step S107.

FIG. 21 is an image diagram illustrating another example of IPMV distribution for an air-conditioning control pattern determined in step S107.

FIG. 22 is a diagram illustrating a configuration example of an air-conditioning system of Modification Example 1.

DETAILED DESCRIPTION

Embodiments of the present disclosure will be described in detail with reference to the drawings. Various specific configurations described in the present embodiments are only examples, and the present disclosure is not limited to the configuration examples described herein. In the embodiments of the present disclosure, communication includes a wireless communication and/or a wired communication. In the present embodiments, the communication may be a communication system using both a wireless communication and a wired communication. The communication system may be configured so that, for example, a wireless communication is used in one section and a wired communication is used in another space. In addition, the communication system may be configured so that a wired communication is used in communication from one device to another device and a wireless communication is used in communication from the other device to the one device.

Embodiment 1

The configuration of an air-conditioning system 1 according to Embodiment 1 will be described. FIG. 1 is a diagram illustrating a configuration example of an air-conditioning system according to Embodiment 1. As shown in FIG. 1 , the air-conditioning system includes an air-conditioning apparatus 10 that conditions air in a room, which is an air-conditioning target space, a user-detecting unit 30 that detects an amount of activity of a user in the room and a position of the user, and an information processing device 2 to which the air-conditioning apparatus 10 and the user-detecting unit 30 are connected for communication. The air-conditioning apparatus 10 and the user-detecting unit 30 are connected to the information processing device 2 via a network 50 for communication. The network 50 may be the Internet, for example.

The user-detecting unit 30 includes an activity-amount-detecting unit 32 that detects an amount of activity of a user in the room and a position-detecting unit 31 that detects a position of the user in the room.

The configuration of the air-conditioning apparatus 10 shown in FIG. 1 will be described. FIG. 2 is a refrigerant circuit diagram illustrating a configuration example of the air-conditioning apparatus shown in FIG. 1 . The air-conditioning apparatus 10 includes a heat-source-side unit 104 that provides a heat source and a load-side unit 103 that conditions air in the room by using the heat source provided by the heat-source-side unit 104. The heat-source-side unit 104 includes a compressor 119, a heat-source-side heat exchanger 116, an expansion valve 117, a fan 114, and a four-way valve 118. The load-side unit 103 includes a load-side heat exchanger 115, a fan 113, an airflow direction adjusting unit 105, and a controller 130.

The airflow direction adjusting unit 105 includes a first flap 4 and a second flap 5 that adjust flow directions of air blown out from the load-side unit 103. The load-side unit 103 is provided with an environment detecting unit 120. The environment detecting unit 120 includes a room temperature sensor 121 that detects a temperature of an indoor air, a humidity sensor 122 that detects a humidity of the indoor air, and a temperature sensor 123 that detects a temperature Tb of air blown out to the room from the load-side unit 103. The load-side unit 103 is also provided with an infrared sensor 140 that detects a distribution of temperatures in an indoor space. The infrared sensor 140 functions as the user-detecting unit 30 shown in FIG. 1 .

The compressor 119, the heat-source-side heat exchanger 116, the expansion valve 117, and the load-side heat exchanger 115 are connected by a refrigerant pipe 110 to form a refrigerant circuit 102 in which refrigerant circulates. The compressor 119, the expansion valve 117, the fan 114, the four-way valve 118, and the airflow direction adjusting unit 105 are connected to the controller 130 for communication. The environment detecting unit 120 and the infrared sensor 140 are connected to the controller 130 for communication.

The compressor 119 compresses sucked refrigerant and then discharges the refrigerant therefrom. The compressor 119 is, for example, an inverter compressor capable of changing capacity. The four-way valve 118 changes a flow direction of the refrigerant flowing in the refrigerant circuit 102. The expansion valve 117 decompresses and thereby expands the refrigerant. The expansion valve 117 is, for example, an electronic expansion valve. The heat-source-side heat exchanger 116 is a heat exchanger that causes heat exchange to be performed between the refrigerant and an outdoor air. The load-side heat exchanger 115 is a heat exchanger that causes heat exchange to be performed between the refrigerant and an indoor air. The heat-source-side heat exchanger 116 and the load-side heat exchanger 115 are, for example, finned tube heat exchangers.

A heat pump is formed when the refrigerant circulates through the refrigerant circuit 102 while being repeatedly compressed and expanded. The load-side unit 103 conditions an indoor air by performing an operation, such as cooling, heating, dehumidification, humidification, moisture holding, or ventilation. Although FIG. 2 indicates that the controller 130 is provided at the load-side unit 103, the installation position of the controller 130 is not limited to the load-side unit 103. The controller 130 may be installed at the heat-source-side unit 104, or may be installed at a position other than the load-side unit 103 and the heat-source-side unit 104. In addition, a temperature sensor (not shown) that detects a condensation temperature and an evaporation temperature may be installed at the air-conditioning apparatus 10.

FIG. 3 is a schematic diagram viewed from a side, illustrating a configuration example of the load-side unit shown in FIG. 2 . The load-side unit 103 is embedded in a ceiling 70. When the fan 113 rotates, a stream of air flowing in the direction indicated by a broken line arrow is formed in the load-side unit 103, and the air is blown into the room via an air outlet 6. The air outlet 6 is provided with the first flap 4 and the second flap 5. The second flap 5 includes a front wing 5 a and a back wing 5 b.

FIG. 4 is a schematic diagram illustrating a relationship between an angle of the first flap shown in FIG. 3 and an air blow direction. As shown in FIG. 4 , the first flap 4 includes wings 4 a to 4 d. In FIG. 4 , for the purpose of explanation, the wings 4 a to 4 d are indicated as viewed through the load-side unit 103 from the top. Suppose that the angle of each of the wings 4 a to 4 d of the first flap 4 is indicated as θh with a front direction (opposite direction of Y-axis arrow) of the load-side unit 103 as a horizontal reference θh0=0°. In FIG. 4 , an air blow direction ad1 with a horizontal direction angle θhl is indicated by a broken line arrow, and an air blow direction ad2 with a horizontal direction angle θh2 is indicated by a solid line arrow.

FIG. 5 is a schematic diagram illustrating a relationship between an angle of the second flap shown in FIG. 3 and an air blow direction. In FIG. 5 , for the purpose of explanation, the front wing 5 a of the second flap 5 shown in FIG. 3 is shown as an enlarged view and the illustration of the back wing 5 b is omitted. With a downward direction (opposite direction of Z-axis arrow) of the load-side unit 103 as a vertical reference Vax, the angle of the front wing 5 a is indicated as θv. In FIG. 5 , an air blow direction ad3 with a vertical direction angle θv1 is indicated by a solid line arrow, and an air blow direction ad4 with a vertical direction angle θv2 is indicated by a broken line arrow.

Note that, although, in Embodiment 1, a case where the load-side unit 103 is of a ceiling embedded type is described, the load-side unit 103 may be of another type, such as a type that is attached to an interior side surface of a ceiling or a type that is attached to a wall. Furthermore, the configuration of the load-side unit 103 shown in FIG. 3 is illustrative of one example, and the configuration of the load-side unit 103 is not limited to the configuration shown in FIG. 3 . The arrangement of the load-side heat exchanger 115 and the fan 113 is not limited to the arrangement shown in FIG. 3 .

The structure for adjusting directions of air blown out from the load-side unit 103 is not limited to the airflow direction adjusting unit 105, which was described with reference to FIGS. 3 to 5 . The airflow direction adjusting unit 105 has two types of vanes, which are the first flap 4 adjusting the angle in the horizontal direction and the second flap 5 adjusting the angle in the vertical direction, but the airflow direction adjusting unit 105 may have one type of a vane that is capable of adjusting the angle in any direction among the combinations of the horizontal direction and the vertical direction. Furthermore, the unit for adjusting directions of air blown out from the load-side unit 103 is not limited to the airflow direction adjusting unit 105, but may be a unit that changes the direction of the air outlet itself. For example, a unit that changes the angles of the air outlet in the vertical direction and the horizontal direction can be considered.

FIG. 6 is a diagram illustrating an example of a range of temperature distribution in a vertical direction to be detected by the infrared sensor shown in FIG. 2 . As with FIG. 5 , the angle in the vertical direction with the vertical reference Vax as a reference is indicated as θv. FIG. 7 is a diagram illustrating an example of a range of temperature distribution in a horizontal direction to be detected by the infrared sensor shown in FIG. 2 . As with FIG. 4 , the angle in the horizontal direction with the horizontal reference θh0 as a reference is indicated as θh. As shown in FIGS. 6 and 7 , the infrared sensor 140 measures a distribution of indoor temperatures in a certain range of vertical direction angle θv and in a certain range of horizontal direction angle θh with respect to the direction of a wall (opposite direction of Y-axis arrow) that the load-side unit 103 faces.

FIG. 8 is an image diagram illustrating an example of a case where a distribution of temperatures detected by the infrared sensor shown in FIG. 2 is shown as a two-dimensional image. For the purpose of explanation, in FIG. 8 , boundaries between walls and boundaries between a wall and the floor or the ceiling are indicated by broken lines. In general, because the walls, floor, and ceiling are made of different materials having different heat conductivities, the temperatures of the walls, the floor, and the ceiling are different from each other and thus their boundaries can be detected in the two-dimensional image showing the distribution of temperatures.

In an image Img shown in FIG. 8 , the higher the temperature, the higher the density of dots becomes. Because a warmer air tends to stay closer to the ceiling side rather than a floor FL, the dot density on the ceiling side becomes higher compared to that on the floor FL side. Because the temperature of the floor FL is low, no dot is shown for the floor FL. From the image Img shown in FIG. 8 , it is found that the position of a person's body can be detected when a person is present in the room because the surface temperature of the body is different from the temperature of the floor FL and that of the walls. The image Img of FIG. 8 indicates a case where the position of a user MA and the position of a user MB in the room are detected. By comparing the dot density indicating the surface temperature of the user MA and that of the user MB, an amount of activity of each of the users can be estimated. In the image Img shown in FIG. 8 , because the dot density of the user MB is higher than that of the user MA, it can be estimated that the amount of activity of the user MB is larger than that of the user MA.

FIG. 9 is a functional block diagram illustrating a configuration example of the controller shown in FIG. 2 . The controller 130 is, for example, a microcomputer. The controller 130 includes a refrigeration cycle control unit 131 and a communication unit 132. In the controller 130, an arithmetic device such as a microcomputer executes software to achieve various functions. The controller 130 may be made of hardware such as a circuit device that achieves various functions.

The refrigeration cycle control unit 131 is configured to control the four-way valve 118 in response to an operation of the load-side unit 103, such as cooling, heating, dehumidification, humidification, moisture holding, or ventilation. The refrigeration cycle control unit 131 is configured to control a refrigeration cycle of the refrigerant circuit 102 based on a room temperature and a set temperature, and a humidity and a set humidity. For example, the refrigeration cycle control unit 131 controls the operation frequency of the compressor 119, the opening degree of the expansion valve 117, and the rotation speeds of the fans 113, 114 so that the room temperature is in a certain range of the set temperature and the humidity is in a certain range of the set humidity. A wind speed W of airflow to be generated by the fan 113 can be selected from three levels, for example, high, medium, and low. The set temperature and the set humidity are set in the controller 130 by a user via a remote controller, which is not shown.

In addition, the refrigeration cycle control unit 131 is configured to transmit, to the communication unit 132, environmental information including the room temperature detected by the room temperature sensor 121 and the humidity detected by the humidity sensor 122. The refrigeration cycle control unit 131 is configured to transmit, to the communication unit 132, operation information including the frequency of the compressor 119, the condensation temperature, the evaporation temperature, and the opening degree of the expansion valve 117. The operation information may include airflow information including the temperature Tb detected by the temperature sensor 123, the horizontal direction angle θh of the first flap 4, the vertical direction angle θv of the second flap 5, and the wind speed W.

Furthermore, the refrigeration cycle control unit 131 is configured to analyze a two-dimensional image of the distribution of temperatures detected by the infrared sensor 140, and transmits, to the communication unit 132, user information, which is a set of position information indicating the position of a user in the room and temperature data indicating the surface temperature of the user. The position information is information indicating a position represented by the horizontal direction angle θh and the vertical direction angle θv with the load-side unit 103 as a reference. When there are a plurality of users in the room, the refrigeration cycle control unit 131 transmits a plurality of pieces of the user information to the communication unit 132. The refrigeration cycle control unit 131 may transmits, to the communication unit 132, data of the two-dimensional image of the temperature distribution detected by the infrared sensor 140 instead of the plurality of pieces of the user information.

Moreover, when receiving information of an air-conditioning control pattern from the communication unit 132, the refrigeration cycle control unit 131 configured to control the airflow direction adjusting unit 105 and the fan 113 according to the air-conditioning control pattern. More specifically, the refrigeration cycle control unit 131 adjusts the temperature, the wind speed, and the wind direction of air to be blown out according to the air-conditioning control pattern.

The air-conditioning control pattern is, for example, a combination of four control parameters, which are the temperature Tb detected by the temperature sensor 123, the horizontal direction angle θh of the first flap 4, the vertical direction angle θv of the second flap 5, and the wind speed W of air to be blown out from the load-side unit 103. A plurality of air-conditioning control patterns are patterns in which at least one of the four control parameters of one pattern is different from the four control parameters of the other patterns. Specific examples for the plurality of the air-conditioning control patterns will be described later.

The communication unit 132 is configured to transmit the environmental information, the operation information, and the user information received from the refrigeration cycle control unit 131 to the information processing device 2. When receiving the data of a two-dimensional image indicating a distribution of temperatures from the refrigeration cycle control unit 131, the communication unit 132 transmits the data of the two-dimensional image to the information processing device 2. When receiving the information of an air-conditioning control pattern from the information processing device 2, the communication unit 132 transmits the received information of the air-conditioning control pattern to the refrigeration cycle control unit 131. The communication unit 132 is configured to transmit and receive information to/from the information processing device 2 according to the Transmission Control Protocol/Internet Protocol (TCP/IP).

Now, one example of hardware of the controller 130 shown in FIG. 9 will be described. FIG. 10 is a hardware configuration diagram illustrating a configuration example of the controller shown in FIG. 9 . When various functions of the controller 130 are executed by hardware, the controller 130 shown in FIG. 9 is a processing circuit 80, as shown in FIG. 10 . Each of the functions of the refrigeration cycle control unit 131 and the communication unit 132 shown in FIG. 9 is achieved by the processing circuit 80.

When each of the functions is executed by hardware, the processing circuit 80 corresponds to, for example, a single circuit, a composite circuit, a programmed processor, a parallel-programmed processor, an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a combination of those circuits. The function of the refrigeration cycle control unit 131 and the function of the communication unit 132 may be achieved by respective processing circuits 80. Alternatively, the function of the refrigeration cycle control unit 131 and the function of the communication unit 132 may be achieved by a single processing circuit 80.

Furthermore, another example of the hardware of the controller 130 shown in FIG. 9 will be described. FIG. 11 is a hardware configuration diagram illustrating another configuration example of the controller shown in FIG. 9 . When various functions of the controller 130 are executed by software, the controller 130 shown in FIG. 9 is formed as a processor 81 and a memory 82, as shown in FIG. 11 . Each of the functions of the refrigeration cycle control unit 131 and the communication unit 132 is achieved by the processor 81 and the memory 82. FIG. 11 indicates that the processor 81 and the memory 82 are connected to each other via a bus 83 such that they can communicate with each other.

When each of the functions is executed by software, the functions of the refrigeration cycle control unit 131 and the communication unit 132 are achieved by software, firmware, or a combination of software and firmware. The software or the firmware is described as a program and is stored in the memory 82. The processor 81 is configured to read out and execute the program stored in the memory 82, to thereby achieve the function of each of the units.

As the memory 82, a read only memory (ROM), a flash memory, an erasable and programmable ROM (EPROM), an electrically erasable and programmable ROM (EEPROM), or another non-volatile semiconductor memory is used, for example. In addition, as the memory 82, a volatile semiconductor memory, such as a random access memory (RAM), may be used. Furthermore, as the memory 82, a detachable recording medium, such as a magnetic disk, a flexible disk, an optical disc, a compact disc (CD), a mini disc (MD), or a digital versatile disc (DVD), may be used.

Next, before explaining the configuration of the information processing device 2 shown in FIG. 1 , a comfort index that is used when the information processing device 2 determines an air-conditioning control pattern for the air-conditioning apparatus 10 will be explained. First, the PMV, which is a type of the comfort index, will be explained.

For humans, a tired feeling and a pleasant feeling during work are caused by physical environmental factors around a person, such as a thermal environment, a visual environment, and an acoustic environment. The thermal environment includes, for example, temperature, humidity, airflow, and radiant temperature. The visual environment includes, for example, lighting. The acoustic environment includes, for example, sound pressure. A composite environment, which is a combination of those environmental factors, affects work compatibility and tiredness of a person working under the environment.

The PMV was developed by Professor Fanger at the Technical University of Denmark as a numerical index for evaluating a comfort level and a thermal sensation of a person in a thermal environment. The PMV was adopted as an International standard (ISO-7730) in 1984. The PMV associates a thermal load of a person's body with a thermal sensation of a person. More specifically, for the PMV, a heat-balance equation for human body is generated by using air-environment-side parameters and human-body-side parameters, and the PMV is calculated by substituting an equation of a skin temperature at which people feels comfortable and a heat transfer amount by sweating into the heat-balance equation. The air-environment-side parameters include, not only an air temperature, but also a radiant temperature, a radiative temperature, a humidity, an airflow and other parameters. The human-body-side parameters include an amount of activity of a person, a clothing amount, an average skin temperature, and other parameters.

The amount of activity is an example of biological information of human, and is expressed by a unit indicating the intensity of activity called Metabolic Equivalent (MET). Various activities are expressed by numerical values using MET. For example, when a person is watching TV while sitting quietly, the intensity of the activity is defined as 1 MET.

Embodiment 1 describes a case where the comfort index is an individual PMV (IPMV) indicating an individual's comfort index. Although a value of the IPMV is based on the PMV, the value does not indicate an average value of thermal sensation for the entire air-conditioning target space but indicates a local thermal sensation for a specific position. The specific position is a position of a person specified in the air-conditioning target space and the local thermal sensation is a thermal sensation for the position. The local thermal sensation is also referred to as a local comfort level. [Equation 1]

IPMV=(0.303e ^(−0.036M)+0.028)×(M−W−Ed−Es−Ere−Cre−R−C)  (1)

The eight variables in Equation 1 will be explained. M is a metabolic rate [W/m²] and W is an amount of mechanical work [W/m²]. Ed is an amount of insensible water loss [W/m²] and Es is an amount of evaporative heat loss [W/m²] from a skin surface by sweating. Ere is an amount of latent heat loss [W/m²] by respiration and Cre is an amount of sensible heat loss [W/m²] by respiration. R is an amount of radiant heat loss [W/m²] and C is an amount of convection heat loss [W/m²].

As shown in Equation 1, the IPMV is a numerical expression of an individual's thermal sensation using the temperature, the humidity, the radiation temperature, and other parameters. A range of the IPMV is from −3 to +3. When IPMV=0, it represents neutral. When IPMV=0, the thermal sensation is defined as comfortable. When IPMV=3, IPMV=2, and IPMV=1, the thermal sensations are defined as hot, warm, and slightly warm, respectively. When IPMV=−3, IPMV=−2, IPMV=−1, the thermal sensations are defined as cold, cool, and slightly cool, respectively. That is, as the IPMV comes closer to zero, the comfort level of an individual becomes improved.

Next, the configuration of the information processing device 2 shown in FIG. 1 will be described. FIG. 12 is a functional block diagram illustrating a configuration example of the controller of the information processing device shown in FIG. 1 . The information processing device 2 includes a storage device 21 that stores an IPMV database, and a controller 22 that obtains a most appropriate air-conditioning control pattern based on the amounts of activity, the positions, and the comfort indexes of a plurality of users in the room and then supplies the obtained pattern to the air-conditioning apparatus 10. The storage device 21 is, for example, a hard disk drive (HDD). The controller 22 is, for example, a microcomputer. Various functions of the controller 22 are achieved by executing software by an arithmetic circuit, such as a microcomputer. A procedure shown in the flowchart (FIG. 18 ), which will be described later, is written in the software.

The controller 22 includes a data acquisition unit 11, a model generation unit 12, an activity amount determination unit 13, a position determination unit 14, an efficiency calculation unit 15, and a control determination unit 16. The storage device 21 stores a standard three-dimensional fluid model for generating an IPMV database. The storage device 21 stores an IPMV database generated by the model generation unit 12. In the IPMV database, a group that includes comfort index distributions each being a distribution of comfort indexes for a user in the room and each corresponding to each of a plurality of air-conditioning control patterns of the air-conditioning apparatus 10 is provided for each of a plurality of amounts of activity.

The data acquisition unit 11 is configured to store, in the storage device 21, environment information, operation information, and user information, which are received from the air-conditioning apparatus 10 at predetermined intervals. The data acquisition unit 11 is configured to store, in the storage device 21 in chronological order, the information received from the air-conditioning apparatus 10 at predetermined intervals, and monitor the operation state of the air-conditioning apparatus 10. The model generation unit 12 is configured to read out environment information and operation information from the storage device 21 and reflect the read information in the standard three-dimensional fluid model to generate an IPMV database. The activity amount determination unit 13 is configured to specify a group corresponding to the amount of activity detected by the infrared sensor 140 for each of the users by referring to the IPMV database.

The position determination unit 14 is configured to extract, for each of the users, a plurality of comfort indexes corresponding to a position detected by the infrared sensor 140, from a plurality of the comfort index distributions in the group specified by the activity amount determination unit 13. The efficiency calculation unit 15 is configured to calculate a comfort efficiency ζ indicating a comprehensive comfort level of users for each of the plurality of the air-conditioning control patterns, based on the plurality of the comfort indexes extracted in correspondence of the detected position of each of the users. The control determination unit 16 is configured to obtain an air-conditioning control pattern that enables the calculated comfort efficiency ζ to be maximum, from the plurality of the air-conditioning control patterns. The control determination unit 16 is configured to transmit the obtained air-conditioning control pattern to the air-conditioning apparatus 10.

The controller 22 is configured to transmit, to the air-conditioning apparatus 10, the air-conditioning control pattern that changes a wind direction and an air volume so that the IPMV for the position at which a user is present becomes close to neutral. The controller 22 is configured to determine the air-conditioning control pattern to bring the IPMV for the position at which a user is present closer to neutral, instead of bringing the PMV for the entire indoor space to neutral. The controller 22 does not use the IPMV for positions at which users are not present as determinants of air-conditioning control patterns. Among the units of the controller 22 shown in FIG. 12 , the configuration of the model generation unit 12 and the configuration of the efficiency calculation unit 15 will be described in detail.

The configuration of the model generation unit 12 shown in FIG. 12 will be described. The values of the eight variables in Equation 1 can be derived by using six parameters, which are a room temperature, a wind speed, a radiation temperature, a humidity, a clothing amount of a user, and an amount of activity of each user. In the IPMV, values of the room temperature, the wind speed, and the radiation temperature correspond to the position of the user. Therefore, in this case, the room temperature is a local temperature, the wind speed is a local wind speed, and the radiation temperature is a local radiation temperature. A method of how to obtain these six values by the model generation unit 12 will be described below.

By using a computational fluid dynamics (CFD), which is an example of numerical fluid analysis, the model generation unit 12 simulates a temperature distribution in an air-conditioning target space for each of the air-conditioning control patterns, and estimates, as the local temperature, the temperature of a specific position from the temperature distribution. The humidity is detected by the humidity sensor 122. The model generation unit 12 obtains information of the humidity from the operation information stored in the storage device 21. By using an analysis result by the CFD, the model generation unit 12 estimates, as the local wind speed, the wind speed at a specific position from the wind speed of air in the entire air-conditioning target space. The local radiation temperature is estimated to be the same as the room temperature. Therefore, the model generation unit 12 obtains a value detected by the room temperature sensor 121 from the operation information stored in the storage device 21.

As the clothing amount, the model generation unit 12 estimates a clo value representing a clothing thermal insulation by using data of the two-dimensional image received from the air-conditioning apparatus 10. More specifically, the model generation unit 12 estimates a skin temperature, an amount of exposed skin, and a surface temperature of clothing for each of the detected users from the data of the two-dimensional image. Then, the model generation unit 12 refers to a clo value table, in which skin temperatures, amounts of exposed skin, and surface temperatures of clothing are associated with do values, to obtain a do value for each user. The storage device 21 stores the clo value table. The model generation unit 12 estimates, as the amount of activity, MET of each user from data of the two-dimensional image received from the air-conditioning apparatus 10. For example, an MET table in which infrared detection values in the data of the two-dimensional image and MET values are associated with each other, is stored in the storage device 21 in advance. The model generation unit 12 refers to the MET table to read out an MET corresponding to the infrared detection value of each user.

For the air-conditioning target space, the model generation unit 12 generates, corresponding to the plurality of the air-conditioning control patterns, an IPMV database for each of the amounts of activity independent of user's position, by using the CFD as a numerical fluid analysis, and stores IPMV databases in the storage device 21.

FIG. 13 is a table illustrating an example in which types of activities and corresponding energy metabolism rates, each representing a typical amount of activity, are listed. The energy metabolism rates are calculated by using Equation 2. According to FIG. 13 , the amount of activity of people asleep is 0.7 MET and the amount of activity of people in quiet sitting is 1 MET.

$\begin{matrix} \left\lbrack {{Equation}2} \right\rbrack &  \\ {{MET} = \frac{{Metabolic}{rate}{during}{certain}{activity}M}{{Metabolic}{rate}{during}{quiet}{sitting}{Ms}}} & (2) \end{matrix}$

One example of calculation processing of the CFD by the model generation unit 12 will be explained. First, the model generation unit 12 creates a three-dimensional model for an air-conditioning target space to be a target of simulation by using a standard three-dimensional fluid model. Next, the model generation unit 12 divides the modeled air-conditioning target space by grid lines, for example. Then, the model generation unit 12 applies an initial requisite as a boundary condition to a result of heat calculation, which corresponds to a pressure, a temperature, and a velocity of fluid, a heat generating body in the space, and an intrusion heat from walls, for each rectangular area formed between grid lines. Furthermore, the model generation unit 12 uses a predetermined turbulence model and a predetermined difference scheme to analyze the pressure, the wind volume, and the temperature in each rectangular area based on the boundary condition, such as intrusion heat from walls and internal heat generation.

In Embodiment 1, the IPMV is calculated corresponding to each of the plurality of the air-conditioning control patterns. The plurality of the air-conditioning control patterns includes 81 combinations of three patterns for the angle θh of the first flap 4, three patterns for the angle θv of the second flap 5, three patterns for the wind speed W, and three patterns for the temperature Tb, for example. That is, Embodiment 1 describes a case where there are 3*3*3*3=81 patterns for the air-conditioning control.

There are three patterns for the horizontal direction angle θh of the first flap 4, which are 30 degrees in the left direction (X-axis arrow direction of FIG. 4 ), zero degrees, and 30 degrees in the right direction (opposite direction to X-axis arrow of FIG. 4 ). There are three patterns for the vertical direction angle θv of the second flap 5, which are θv=20 degrees, 45 degrees, and 60 degrees. There are three wind speed W patterns of high, medium, and low. There are three patterns for the temperature Tb of air blown out from the load-side unit 103, which are high, medium, and low.

By considering not a position in the air-conditioning target space but the entire air-conditioning target space, the model generation unit 12 performs the CFD analysis for 81 air-conditioning control patterns for each amount of activity, such as 1 MET and 2 MET, and generates an IPMV distribution, which is a distribution of the IPMVs in the air-conditioning target space. For the IPMV distribution, the air-conditioning target space is divided into a plurality of rectangular areas by the CFD analysis, and the IPMV corresponding to each of the rectangular areas is stored in the storage device 21. For example, the model generation unit 12 generates IPMV distributions for 81 patterns for an amount of activity of 1 MET and stores the distributions as one group, and generates IPMV distributions for 81 patterns for an amount of activity of 2 MET and stores the distributions as another group. In this manner, the model generation unit 12 generates a plurality of groups each corresponding to each of the plurality of the amounts of activity, and stores the plurality of the groups in the storage device 21 as the IPMV databases. Although, in Embodiment 1, a case where the amounts of activity are changed at an interval of 1.0, such as 1 MET and 2 MET, is described, the interval is not limited to 1.0. The interval for the amounts of activity may be 0.1 or 0.5.

By using Equation 3, the efficiency calculation unit 15 calculates the comfort efficiency ζ for each of the plurality of the air-conditioning control patterns by using the information on the positions of the users in the room and information on the amounts of activity of the users.

[Equation 3]

ζ=(1−2|IPMV₁|)×(1−2|IPMV₂|1)× . . . ×(1−2|IPMV_(K)|)×100%  (3)

In Equation 3, k represents an identification number, which is different for each user, and K represents the number of users in the room. In Embodiment 1, K is equal to or larger than two. Because a target value for the individual comfort index IPMV is set to be within a range of plus/minus 0.5, |IPMVk| is set to 0.5 when |IPMVk| is larger than 0.5.

The comfort efficiency ζ indicates how close the thermal sensations of the plurality of the users are to the neutral value (individual IPMV=0). The comfort efficiency ζ indicates a comprehensive comfort level of the users in a room. It is considered that the higher the comfort efficiency ζ (maximum 100%), the more the plurality of the users in the room can satisfy the comfort level. That is, the comfort efficiency ζ=100% indicates that the plurality of the users feel comfortable, and the comfort efficiency ζ=0% indicates that the plurality of the users feel uncomfortable. The control determination unit 16 obtains the air-conditioning control pattern that enables the comfort efficiency ζ to be maximum from the 81 air-conditioning control patterns based on the comfort efficiencies ζ.

One example of hardware of the controller 22 shown in FIG. 12 will be described. FIG. 14 is a hardware configuration diagram illustrating a configuration example of the arithmetic device shown in FIG. 12 . When the functions of the controller 22 are executed by software, the controller 22 shown in FIG. 12 is made up of a processor 91, such as a central processing unit (CPU), and a memory 92, as shown in FIG. 14 . Each of the functions of the data acquisition unit 11, the model generation unit 12, the activity amount determination unit 13, the position determination unit 14, the efficiency calculation unit 15, and the control determination unit 16 is achieved by the processor 91 and the memory 92. FIG. 14 indicates that the processor 91 and the memory 92 are connected to each other via a bus 93 such that they can communicate with each other. The processor 91 and the memory 92 are connected to the storage device 21 shown in FIG. 12 via the bus 93. The memory 92 functions as a primary storage device and the storage device 21 functions as a secondary storage device.

When each of the functions is executed by software, the functions of the data acquisition unit 11, the model generation unit 12, the activity amount determination unit 13, the position determination unit 14, the efficiency calculation unit 15, and the control determination unit 16 are achieved by software, firmware, or a combination of software and firmware. The software or the firmware is described as a program and is stored in the memory 92. The processor 91 is configured to read out and execute the program stored in the memory 92, to thereby achieve the functions of the units. The memory 92 has, for example, a similar configuration to that of the memory 82, and a detailed description thereof will be omitted.

Note that, the model generation unit 12 may learn in advance a calculation method for IPMV by a neural network, and may estimate IPMVs in an air-conditioning target space from input conditions, such as a building load, a region, and a preference of a user.

Furthermore, the temperature Tb of air blown out from the load-side unit 103 linearly changes according to a load of a building and the operation frequency of the compressor 119. For this reason, the model generation unit 12 may learn a most appropriate combination of the temperature Tb of air blown out from the load-side unit 103, the angles θh and θv, and the wind speed W based on input conditions, such as a building load, a region, and a preference of a user, and may narrow down, by the neural network, the air-conditioning control patterns to be selected. In this case, because the control determination unit 16 selects the most appropriate air-conditioning control pattern from the limited number of the air-conditioning control patterns, processing for determining the air-conditioning control pattern can be performed smoothly. The preference of a user is, for example, a tendency of thermal sensation that the user has.

More specifically, the storage device 21 stores, in chronological order, combination data, which is a combination of input conditions including a thermal load of the building at which the air-conditioning apparatus 10 is installed and the air-conditioning control pattern that enables the comfort efficiency ζ to be maximum. Then, the control determination unit 16 narrows down air-conditioning control patterns to be selected, among the plurality of the air-conditioning control patterns based on a plurality pieces of combination data stored in chronological order. In this case, the input conditions may include, in addition to the thermal load of the building, a region at which the air-conditioning apparatus 10 is installed, climate data of the region, an amount of insolation on the building, and information on tendencies of thermal sensations of the plurality of the users.

Moreover, the model generation unit 12 may update IPMV distributions in the IPMV databases as follows. The model generation unit 12 estimates a refrigeration capacity of the air-conditioning apparatus 10 from the operation information including the frequency of the compressor 119, the condensation temperature, the evaporation temperature, and the opening degree of the expansion valve 117. Then, the model generation unit 12 reflects the estimated refrigeration capacity and a state of airflow estimated by the temperature Tb, the horizontal direction angle θh, the vertical direction angle θv, and the wind speed W in the IPMVs of each of the groups stored for each of the plurality of the amounts of activity. In this case, the IPMV databases are updated to the latest state in response to a change in the operation state of the air-conditioning apparatus 10.

Next, a control method of the information processing device 2 of Embodiment 1 will be described. FIG. 15 is a layout diagram illustrating an example of an air-conditioning target space in which the air-conditioning apparatus shown in FIG. 1 conditions air. FIG. 15 shows the position of each piece of furniture and the positions of two users in the room. Here, as shown in FIG. 15 , a case where a user MA and a user MB are present in the room will be described. The vertical axis shows a Y-axis coordinate, and the horizontal axis shows an X-axis coordinate. FIG. 16 is a table illustrating an example of activity amounts and positions of the users. The amount of activity of the user MA is 1 MET, and that of the user MB is 2 MET.

FIG. 17 is a schematic diagram illustrating an operation procedure of the information processing device according to Embodiment 1. Here, n of nMET is an integer of 2 or greater. FIG. 18 is a flowchart illustrating an operation procedure of the information processing device according to Embodiment 1. In step S101, the data acquisition unit 11 obtains environment information from the air-conditioning apparatus 10. The data acquisition unit 11 stores the obtained environment information in the storage device 21.

In step S102, the data acquisition unit 11 obtains operation information from the air-conditioning apparatus 10. The data acquisition unit 11 stores the obtained operation information in the storage device 21. The operation information includes the frequency of the compressor 119, the condensation temperature, the evaporation temperature, and the opening degree of the expansion valve 117. In addition, the operation information includes information on airflow including the temperature Tb detected by the temperature sensor 123, the horizontal direction angle θh of the first flap 4, the vertical direction angle θv of the second flap 5, and the wind speed W.

In step S101 or step S102, the data acquisition unit 11 obtains, as user information, data of the two-dimensional image detected by the infrared sensor 140 from the air-conditioning apparatus 10, and stores the data in the storage device 21. The model generation unit 12 generates an IPMV database by using the information stored in the storage device 21. The model generation unit 12 stores the generated IPMV database in the storage device 21. FIG. 17 shows IPMV databases for each of the amounts of activity, in which 81 patterns of IPMV distributions are provided.

In step S103, the activity amount determination unit 13 refers to the data of the two-dimensional image stored in the storage device 21 to obtain information on the amount of activity for each user. Here, the activity amount determination unit 13 estimates the amount of activity for the user MA as 1 MET and the amount of activity for the user MB as 2 MET.

In step S104, the position determination unit 14 refers to the data of the two-dimensional image stored in the storage device 21 to obtain information on the position of each user. Here, the position determination unit 14 determines that the coordinates of the position of the user MA are (2, 7), and the coordinates of the position of the user MB are (7, 9).

In step S105, the efficiency calculation unit 15 reads out the group of 1 MET and the group of 2 MET from the IPMV databases based on the estimation results of the activity amount determination unit 13. Then, the efficiency calculation unit 15 reads out 81 IPMVs for the position of the coordinates (2, 7) for the group of 1 MET based on the determination result of the position determination unit 14. In addition, the efficiency calculation unit 15 reads out 81 IPMVs for the position of the coordinates (7, 9) for the group of 2 MET based on the determination result of the position determination unit 14. At the time, the efficiency calculation unit 15 reads out the IPMV at a predetermined height (for example, 1.3 meters above the floor) in the air-conditioning target space in each of the IPMV distributions. Then, the efficiency calculation unit 15 assigns 81 IPMVs of the user MA and 81 IPMVs of the user MB to Equation 3, and calculates 81 comfort efficiencies ζ (step S106).

In step S107, the control determination unit 16 determines the air-conditioning control pattern having the highest comfort efficiency ζ among the 81 air-conditioning control patterns. At the time, as selection conditions for air-conditioning control patterns, not only a condition that the comfort efficiency ζ becomes maximum but also a condition that the IPMV of each user falls within a range of plus/minus 0.5 may be included.

In step S108, the control determination unit 16 transmits the information on the air-conditioning control pattern determined in step S107 to the air-conditioning apparatus 10. When receiving the information on the air-conditioning control pattern from the information processing device 2, the controller 130 of the air-conditioning apparatus 10 controls at least one of the compressor 119, the fan 113, and the airflow direction adjusting unit 105 according to the air-conditioning control pattern. For example, to change the temperature of air to be blown out from the load-side unit 103, the refrigeration cycle control unit 131 changes the operation frequency of the compressor 119. To change the wind speed W, the refrigeration cycle control unit 131 changes the rotation speed of the fan 113. To change the angle θh, the refrigeration cycle control unit 131 changes the angle θh of the first flap 4. To change the angle θv, the refrigeration cycle control unit 131 changes the angle θv of the second flap 5.

In step S109, the data acquisition unit 11 determines whether or not a fixed period of time has elapsed. When it is determined that the fixed period of time has not elapsed yet, the controller 22 enters a standby state. When the determination of step S109 indicates that the fixed period of time has elapsed, the controller 22 returns to the process of step S101.

FIG. 19 is a table illustrating an example of calculation results of the comfort efficiency. FIG. 19 shows the IPMV for the amount of activity of 1 MET, the IPMV for the amount of activity of 2 MET, and the comfort efficiency ζ for each of the air-conditioning control patterns. The numbers in the leftmost column of the table shown in FIG. 19 are identification numbers of the air-conditioning control patterns. Referring to the table shown in FIG. 19 , the air-conditioning control pattern that enables the comfort efficiency ζ to be maximum is the air-conditioning control pattern of Number. 16.

FIG. 20 is an image diagram illustrating an example of IPMV distribution for a case of the air-conditioning control pattern determined in step S107. FIG. 20 shows the IPMV distribution for the amount of activity of 1 MET in the air-conditioning control pattern of No. 16. FIG. 21 is an image diagram illustrating another example of IPMV distribution fora case of the air-conditioning control pattern determined in step S107. FIG. 21 shows the IPMV distribution for the amount of activity of 2 MET in the air-conditioning control pattern of No. 16.

As shown in FIGS. 20 and 21 , in the air-conditioning control pattern of No. 16, the IPMV of the user MA having an amount of activity of 1 MET and the IPMV of the user MB having an amount of activity of 2 MET are visualized. In FIGS. 20 and 21 , the higher the density of dots, the farther the value of the IPMV is away from the neutral to the minus plus side, and the lower the density of dots, the farther the value of the IPMV is away from the neutral to the minus side. In FIG. 20 , the IPMV at the position of the user MA is close to zero. In FIG. 21 , the IPMV is larger than zero in a wide area in the room but it can be recognized that the IPMV around the coordinate position (7, 7), which is near the position of the user MB, is close to zero. This is because air supplied from the load-side unit 103 is controlled to be blown toward the coordinate position (7, 7) and thus the value of the IPMV is lowered. As a result, the IPMVs can be brought to a comfortable range quickly and can be kept stable so that the IPMVs of the plurality of the users, which are the user MA and the user MB, become closer to the neutral.

Note that, although the flowchart of FIG. 18 indicates that the processing returns to step S101, the processing may return to step S103 after a fixed period of time has elapsed in step S109. In this case, in step S103, the data acquisition unit 11 obtains, as user information, data of the two-dimensional image detected by the infrared sensor 140 from the air-conditioning apparatus 10. When the IPMV databases created in the storage device 21 are suitable for the air-conditioning apparatus 10 and the air-conditioning target space, frequent update of the databases is not required. In this case, a load for the arithmetic processing of the model generation unit 12 is reduced.

In addition, in step S109, the activity amount determination unit 13 and the position determination unit 14 may monitor the data of the two-dimensional image, which is detected by the infrared sensor 140 and obtained from the air-conditioning apparatus 10. When the activity amount determination unit 13 determines, in a fixed period of time, that the amount of activity of a user is not constant and/or where the position determination unit 14 cannot determine the presence or absence of a user in the room in a fixed period of time, the direction of air blown out from the load-side unit 103 may be changed. More specifically, the control determination unit 16 transmits, to the air-conditioning apparatus 10, control information that causes the horizontal direction angle of the first flap 4 and/or the vertical direction angle of the second flap 5 to periodically change in a swinging motion. For example, the swinging motion of the first flap 4 is motion in which the first flap 4 swings in the right and left directions with respect to the horizontal reference θh0, in cycles of 20 seconds. In this case, the environment information and the operation information received from the air-conditioning apparatus 10 by the information processing device 2 are changed, and thus the controller 22 can easily recognize the amount of activity and the position of a user.

Furthermore, in Embodiment 1, although the efficiency calculation unit 15 calculates the comfort efficiency ζ for each air-conditioning control pattern by using Equation 3 when the control determination unit determines the air-conditioning control pattern in step S107 shown in FIG. 18 , the way to determine the air-conditioning control pattern is not limited to this evaluation method. The efficiency calculation unit 15 may use the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to determine the air-conditioning control pattern that enables the comprehensive comfort level of the plurality of the users to be maximum. In Embodiment 1, because the evaluation method using Equation 3 requires a fewer calculation amount compared to the TOPSIS, a load for the arithmetic processing of the controller 22 is reduced.

The air-conditioning system 1 of Embodiment 1 includes the air-conditioning apparatus 10, the user-detecting unit 30 detecting the amount of activity for each of the plurality of the users and the position for each of the plurality of the users, the storage device 21, and the controller 22. The storage device 21 stores, for each of the plurality of the amounts of activity, a group that includes a plurality of comfort index distributions each being a distribution of comfort indexes each indicating a user comfort level in the air-conditioning target space and each corresponding to each of the plurality of the air-conditioning control patterns of the air-conditioning apparatus 10. The controller 22 includes the activity amount determination unit 13, the position determination unit 14, the efficiency calculation unit 15, and the control determination unit 16. The activity amount determination unit 13 specifies the group corresponding to the amount of activity detected by the user-detecting unit 30 for each of the users. The position determination unit 14 extracts, from the plurality of the comfort index distributions in the specified group, a plurality of the comfort indexes corresponding to the position detected by the user-detecting unit 30. The efficiency calculation unit 15 calculates the comfort efficiency ζ indicating a comprehensive comfort level of users for each of the plurality of the air-conditioning control patterns based on the plurality of the comfort indexes extracted in correspondence of the detected position of each of the users. The control determination unit 16 obtains, from the plurality of the air-conditioning control patterns, the air-conditioning control pattern that enables the calculated comfort efficiency ζ to be maximum.

According to Embodiment 1, the group that includes the comfort index distributions in the air-conditioning target space each corresponding to each of the plurality of the air-conditioning control patterns is determined corresponding to the amount of activity of each user in the air-conditioning target space. In addition, the plurality of the comfort indexes are extracted from the plurality of the comfort index distributions in the group, corresponding to the position of each user in the air-conditioning target space. Then, based on the plurality of the comfort indexes for each user, the air-conditioning control pattern that enables the comfort efficiencies of the plurality of the users to be maximum is obtained from the plurality of the air-conditioning control patterns. Because the air-conditioning apparatus conditions air according to the air-conditioning control pattern that enables the comfort efficiencies of the plurality of the users to be maximum, the comfortableness can be improved for the plurality of the users.

Note that, although, in Embodiment 1 described above, a case where the infrared sensor 140 functions as a user-detecting unit 20 is described, the user-detecting unit 20 is not limited to the infrared sensor 140. For example, the activity-amount-detecting unit 32 may be a wearable sensor. A case where the activity-amount-detecting unit 32 is a wearable sensor will be described below.

Modification Example 1

FIG. 22 is a diagram illustrating a configuration example of an air-conditioning system of Modification Example 1. In the configuration shown in FIG. 22 , the same features as those described in FIG. 1 are denoted by the same reference signs, and their detailed descriptions will be omitted.

An air-conditioning system 1 a includes the air-conditioning apparatus 10 having the position-detecting unit 31, the information processing device 2, an access point (AP) 60, and a wearable terminal 40 worn by each user. The AP 60 is installed in a room, which is an air-conditioning target space of the air-conditioning apparatus 10. The AP 60 includes a short-range wireless communication unit (not shown), such as Bluetooth (registered trademark), and a network communication unit (not shown) that supports a communication protocol of the network 50. The communication protocol is the TCP/IP, for example. The position-detecting unit 31 is, for example, the infrared sensor 140 shown in FIG. 2 .

The wearable terminal 40 is provided for each user. The wearable terminal 40 is a watch or a bracelet, for example. The wearable terminal 40 includes the activity-amount-detecting unit 32 that detects the pulse of the user at predetermined intervals as the amount of activity of the user. The skin temperature may be used as the amount of activity. In addition, the wearable terminal 40 includes a memory (not shown) that stores a terminal identifier, which is difference for each terminal, and a program, and a CPU (not shown) that executes processing according to the program.

When the activity-amount-detecting unit 32 detects the amount of activity of the user, the CPU (not shown) of the wearable terminal 40 transmits user information including the information on the amount of activity and the terminal identifier to the information processing device 2 via the AP 60 and the network 50. The memory (not shown) of the wearable terminal 40 may store the coordinates of the installation position of the AP 60. The CPU (not shown) of the wearable terminal 40 estimates the distance from the installation position of the AP 60 by referring to the intensity of the radio wave from the AP 60. Then, the CPU (not shown) of the wearable terminal 40 adds, as the position information of the user, the information of the estimated position to the user information. For example, when a plurality of APs 60 are installed in the room, the CPU (not shown) of the wearable terminal 40 compares the intensities of radio waves from the plurality of the APs 60, and can thus accurately estimate the position of the user in the room. The information processing device 2 correlates the user information received form the wearable terminal 40 with the position of user detected by the position-detecting unit 31.

In Modification Example 1 also, the information processing device 2 can determine the most appropriate air-conditioning control pattern from the plurality of the air-conditioning control patterns according to the procedure shown in FIG. 18 . In a case of Modification Example 1, because the wearable terminal 40 worn by each user detects an amount of activity of the user, the amount of activity can be detected more accurately. As a result, a more suitable air-conditioning can be performed for the amount of activity of each of the plurality of the users. 

1. An air-conditioning system, comprising: an air-conditioning apparatus conditioning air in an air-conditioning target space; a user-detecting unit detecting, for a plurality of users in the air-conditioning target space, an amount of activity of each of the plurality of the users and a position of each of the plurality of the users in the air-conditioning target space; a storage device storing, for each of a plurality of amounts of activity, a group including a plurality of comfort index distributions each being a distribution of comfort indexes each indicating a user comfort level in the air-conditioning target space, the plurality of the comfort index distributions each corresponding to each of a plurality of air-conditioning control patterns of the air-conditioning apparatus; and a controller configured to obtain, from the plurality of the air-conditioning control patterns, an air-conditioning control pattern that enables a comfort efficiency of each of the plurality of the users to be maximum, by specifying the group corresponding to the amount of activity detected by the user-detecting unit for each of the users, extracting, from the plurality of the comfort index distributions in the specified group, a plurality of the comfort indexes corresponding to a position detected by the user-detecting unit, and, based on the plurality of the comfort indexes extracted in correspondence of the detected position of each of the users, calculating the comfort efficiency indicating a comprehensive comfort level of users for each of the plurality of the air-conditioning control patterns.
 2. The air-conditioning system of claim 1, wherein the user-detecting unit is an infrared sensor.
 3. The air-conditioning system of claim 1, wherein the user-detecting unit includes a wearable terminal provided for each of the users and detecting the amount of activity of each of the users, and an infrared sensor detecting the position of each of the users in the air-conditioning target space.
 4. A method for controlling an air-conditioning apparatus by a controller being connected to a user-detecting unit detecting, for a plurality of users in the air-conditioning target space, an amount of activity of each of the plurality of the users and a position of each of the plurality of the users in the air-conditioning target space, and also to a storage device, the method comprising: storing in the storage device, for each of a plurality of amounts of activity, a group including a plurality of the comfort index distributions each being a distribution of comfort indexes each indicating a user comfort level in the air-conditioning target space, the plurality of the comfort index distributions each corresponding to each of a plurality of air-conditioning control patterns of the air-conditioning apparatus; specifying the group corresponding to the amount of activity detected by the user-detecting unit for each of the users; extracting, from the plurality of the comfort index distributions in the specified group, a plurality of the comfort indexes corresponding to a position detected by the user-detecting unit for each of the users; calculating a comfort efficiency indicating a comprehensive comfort level of the plurality of the users for each of the plurality of the air-conditioning control patterns based on the plurality of the comfort indexes extracted in correspondence of the detected position of each of the users; and obtaining, from the plurality of the air-conditioning control patterns, an air-conditioning control pattern that enables the calculated comfort efficiency to be maximum.
 5. The method for controlling an air-conditioning apparatus of claim 4, wherein the comfort efficiency for each of the plurality of the air-conditioning control patterns is calculated by equation: ζ=(1−2|IPMV₁|)×(1−2|IPMV₂|)× . . . ×(1−2|IPMV_(k)|)× . . . (1−2|IPMV_(K)|)×100% wherein k represents an identification number different for each of the plurality of the users, IPMVk represents the comfort index of the user having an identification number of k, K represents an integer of 2 or greater, and ζ represents the comfort efficiency.
 6. The method for controlling an air-conditioning apparatus of claim 4, wherein there are four control parameters of a temperature of air blown out from a load-side unit provided at the air-conditioning apparatus, a horizontal direction angle of the air blown out from the load-side unit, a vertical direction angle of the air blown out from the load-side unit, and a wind speed of the air blown out from the load-side unit, and the plurality of the air-conditioning control patterns are made by combining the four control parameters such that at least one of the four control parameters is different for each of the plurality of the air-conditioning control patterns.
 7. The method for controlling an air-conditioning apparatus of claim 6, wherein the controller stores, in chronological order, combination data, which is a combination of input conditions including a thermal load of a building at which the air-conditioning apparatus is installed and the air-conditioning control pattern that enables the comfort efficiency to be maximum for the plurality of the users, and narrows down air-conditioning control patterns to be selected among the plurality of the air-conditioning control patterns based on a plurality of pieces of the combination data stored in chronological order.
 8. The method for controlling an air-conditioning apparatus of claim 7, wherein the input conditions include, in addition to the thermal load of the building, a region at which the air-conditioning apparatus is installed, climate data of the region, an amount of insolation on the building, and information on tendencies of thermal sensations of the plurality of the users.
 9. The method for controlling an air-conditioning apparatus of claim 6, wherein the controller receives operation information including a frequency of a compressor, a condensation temperature, an evaporation temperature, and an opening degree of an expansion valve from the air-conditioning apparatus, estimates a refrigeration capacity of the air-conditioning apparatus based on the received operation information, and reflects the estimated refrigeration capacity and a state of airflow estimated based on the temperature of the air, the horizontal direction angle, the vertical direction angle, and the wind speed, in each of the comfort index distributions of the plurality of the groups stored for each of the plurality of the amounts of activity.
 10. The method for controlling an air-conditioning apparatus of claim 4, wherein in each of the comfort index distributions, the air-conditioning target space is divided into a plurality of areas, and a value of the comfort index corresponding to each of the areas is stored in the storage device.
 11. The method for controlling an air-conditioning apparatus of claim 4, wherein when the amount of activity detected by the user-detecting unit is not constant in a fixed period of time and/or when a presence or absence of a user in the air-conditioning target space cannot be determined in a fixed period of time, the controller causes the air-conditioning apparatus to perform a swinging operation by periodically changing the horizontal direction angle and/or the vertical direction angle of an air blow direction.
 12. The method for controlling an air-conditioning apparatus of claim 4, wherein the user-detecting unit is an infrared sensor.
 13. The method for controlling an air-conditioning apparatus of claim 4, wherein the user-detecting unit includes a wearable terminal provided for each of the users and detecting the amount of activity of each of the users and an infrared sensor detecting the position of each of the users in the air-conditioning target space. 